Pre-diabetes
Conditions
Keywords
Prediabetes, Glucose management, Feedback, Narrative education, Artificial intelligence, Contingency-shaped learning
Brief summary
The objective of this project is to develop a behavioral intervention that combines wearable continuous glucose monitoring (CGM) with smartphone feedback and educational video clips generated by artificial intelligence (AI) software to improve glycemic control among individuals with pre-diabetes. The goal is to prevent transition to type 2 diabetes.
Detailed description
Video narratives will be provided by Latino community health workers, known as Promotores de Salud (PdS), who will wear and experience the continuous glucose monitoring (CGM) system and its glycemic variability feedback. Study 1 (G1) is a Phase 0 intervention development study, enrolling a sample of 20 Spanish- and/or English-speaking PdS who test positive for pre-diabetes via a finger prick screening. Participants will wear CGM devices for 20 days, during which they will record daily narratives about their experiences with the CGM feedback and their glucose variability. Structured interviews between staff and participants will explore the benefits and barriers of CGM use. These recorded video clips will serve as the foundation for educational cinematic smartphone videos for future interventions. Artificial intelligence (AI) tools will be used to translate the text, audio, and video clips into various languages for broad dissemination. Blood glucose levels in mg/dL will be recorded continuously over the wear period.
Interventions
DEVICEThe continuous glucose monitoring system
CGM device worn on back of the arm and glucose readings are shown on the participant's smartphone as a continuous data stream.
Sponsors
University of Southern California
National Institute on Minority Health and Health Disparities (NIMHD)
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE
Masking description
The CGM system feedback is unmasked. The CGM is automatically recorded and does not require an outcomes assessor.
Intervention model description
A case series of participants wear an unmasked CGM sensor for a condition lasting 20 days while recording daily narratives of their experience.
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Prediabetes by finger prick blood A1C% * Centers for Disease Control and Prevention (CDC) prediabetes risk test score of 5 or higher * Willingness to wear CGM sensor * Latino community health worker
Exclusion criteria
* Currently pregnant * Less than 18 years of age, which is adult in California * Diagnosed with any disorder that interferes with glucose * Influential medical disorder/event affecting ability to participate in study * Incompatible smartphone device not pairing with Dexcom G6 app
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Mean Glucose (mg/dL) From Baseline | Up to 20 days of continuous CGM wear, comprising two sequential 10-day assessment periods (baseline Phase A and subsequent Phase B). | Mean glucose was derived from continuous glucose monitoring (CGM) data obtained from the Dexcom Clarity system. Raw glucose values were processed and analyzed using the R statistical software package iglu to generate the full CGM variability metrics panel. For each participant, mean glucose was calculated separately for each 10-day assessment period. The outcome measure represents the change in mean glucose, defined as the difference between the baseline (Phase A) 10-day assessment period and the subsequent (Phase B) 10-day assessment period. |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORDavid S Black, PhD MPH
University of Southern California
Participant flow
Recruitment details
Recruitment and preliminary screening activities occurred between 5/24/2024 and 8/30/2024, using baseline screening telephone calls. The Study Start Date of 6/1/2024 reflects the date on which the first participant was formally enrolled in the study. The target population included 20 community health workers who had been actively working within the past six months, were diagnosed with prediabetes, and primarily resided in Los Angeles County.
Baseline characteristics
| Characteristic | — |
|---|---|
| Age, Continuous | 50.0 years |
| Body Mass Index | 31.8 kg/m² |
| Centers for Disease Control and Prevention (CDC) prediabetes risk score Scored 5 or higher | 19 Participants |
| Centers for Disease Control and Prevention (CDC) prediabetes risk score Scored under 5 | 4 Participants |
| Current employment status Employed | 18 Participants |
| Current employment status Homemaker | 2 Participants |
| Current employment status Retired | 2 Participants |
| Current employment status Student | 0 Participants |
| Current employment status Unemployed | 1 Participants |
| Ethnicity (NIH/OMB) Hispanic or Latino | 23 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 0 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 0 Participants |
| HbA1c (%) HbA1c < 5.7% | 11 Participants |
| HbA1c (%) HbA1c ≥ 5.7% | 12 Participants |
| Health insurance Private | 5 Participants |
| Health insurance Public | 17 Participants |
| Health insurance Self-cash paying | 1 Participants |
| Highest level of education College Degree or Higher | 11 Participants |
| Highest level of education High School or Less | 11 Participants |
| Highest level of education Some College or Vocational Training | 1 Participants |
| Physical Activity Level (International Physical Activity Questionnaire [IPAQ]) High | 10 Participants |
| Physical Activity Level (International Physical Activity Questionnaire [IPAQ]) Low | 6 Participants |
| Physical Activity Level (International Physical Activity Questionnaire [IPAQ]) Moderate | 7 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants |
| Race (NIH/OMB) Black or African American | 0 Participants |
| Race (NIH/OMB) More than one race | 20 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants |
| Race (NIH/OMB) White | 3 Participants |
| Region of Enrollment United States | 23 participants |
| Self-reported history of prediabetes No | 9 Participants |
| Self-reported history of prediabetes Yes | 14 Participants |
| Sex: Female, Male Female | 21 Participants |
| Sex: Female, Male Male | 2 Participants |
| Total household income $10,000 to $29,999 | 7 Participants |
| Total household income $150,000 or more | 0 Participants |
| Total household income $30,000 to $49,999 | 9 Participants |
| Total household income $50,000 to $69,999 | 3 Participants |
| Total household income $70,000 to $89,999 | 1 Participants |
| Total household income $90,000 to $149,999 | 1 Participants |
| Total household income Less than $10,000 | 2 Participants |
Adverse events
| Event type | EG000 affected / at risk |
|---|---|
| deaths Total, all-cause mortality | 0 / 23 |
| other Total, other adverse events | 4 / 23 |
| serious Total, serious adverse events | 0 / 23 |
Outcome results
None listed